Triple
T25256560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEMA 1999 |
E633187
|
entity |
| Predicate | replacedLawNature |
P160852
|
FINISHED |
| Object | criminal law statute |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: criminal law statute | Statement: [FEMA 1999, replacedLawNature, criminal law statute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedLawNature Context triple: [FEMA 1999, replacedLawNature, criminal law statute]
-
A.
legalReformer
Indicates that an entity works to change, improve, or modernize laws or legal systems.
-
B.
legalRulingNature
Indicates the type or character of a legal ruling, such as its form, basis, or procedural nature.
-
C.
replacedInReform
Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.
-
D.
replacedByInLawEnforcement
Indicates that one entity has been superseded or taken over by another entity within a law enforcement context, such as in role, function, or authority.
-
E.
convertsLaw
Indicates that one entity transforms or translates a law from one form, system, or representation into another.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f60ac643108190ae81561267155791 |
completed | May 2, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f606c15af88190958856a9e467b826 |
completed | May 2, 2026, 2:14 p.m. |
Created at: April 21, 2026, 1:13 p.m.